Small extrachromosomal circular DNA in amyotrophic lateral sclerosis matter

Comprehensive studies identify motor neuron spectrum disorders including amyotrophic lateral sclerosis(ALS)as globally rising fatal disorders with the highest prevalence in aging populations,influenced by ethnicity and ancestry(GBD 2016 Motor Neuron Disease Colla borators,2018).While~10% of diagnoses involve a family history(fALS),most cases are considered sporadic(sALS).However,population-based studies suggest that even cases without a common index mutation impart heritability(Ryan et al.,2019),indicating a crucial role of rare and as yet unknown genetic denominators.

Taxon sampling and the accuracy of phylogenetic analyses

Appropriate and extensive taxon sampling is one of the most important determinants of accurate phylogenetic estimation. In addition, accuracy of inferences about evolutionary processes obtained from phyloge-netic analyses is improved significantly by thorough taxon sampling efforts. Many recent efforts to improve phylogenetic estimates have focused instead on increasing sequence length or the number of overall characters in the analysis, and this often does have a beneficial effect on the accuracy of phylogenetic analyses. However, phylogenetic analyses of few taxa (but each represented by many characters) can be subject to strong systematic biases, which in turn produce high measures of repeatability (such as bootstrap proportions) in support of incor-rect or misleading phylogenetic results. Thus, it is important for phylogeneticists to consider both the sampling of taxa, as well as the sampling of characters, in designing phylogenetic studies. Taxon sampling also improves estimates of evolutionary parameters derived from phylogenetic trees, and is thus important for improved applica-tions of phylogenetic analyses. Analysis of sensitivity to taxon inclusion, the possible effects of long-branch attraction, and sensitivity of parameter estimation for model-based methods should be a part of any careful and thorough phylogenetic analysis. Furthermore, recent improvements in phylogenetic algorithms and in computa-tional power have removed many constraints on analyzing large, thoroughly sampled data sets. Thorough taxon sampling is thus one of the most practical ways to improve the accuracy of phylogenetic estimates, as well as the accuracy of biological inferences that are based on these phylogenetic trees.

Transcriptome and Functional Analysis of Fiber-related Gene Expression in Cotton

Fiber cell initiation is a complex process involving many pathways,including phytohormones and components for transcriptional and posttranscriptional regulation.Here we report expression

The Locus PgaABCD of Acinetobacter junii Putatively Responsible for Poly-β-(1,6)-N-Acetylglucosamine Biosynthesis Might Be Related to Biofilm Formation: A Computational Analysis

Poly-β-(1,6)-N-acetylglucosamine (PNAG), the chief mediator of intercellular adhesion in many bacteria, plays an important role in biofilm formation. The pgaABCD locus was recognized from the whole genome sequence of A. junii SH205. The enzyme glycosyltransferase, PgaC, catalyzes the production of PNAG with N-acetyl-D-glucosamine monomer. In this study, the possibility of PNAG biosynthesis in A. junii SH205 with its own PgaC was explored with the aid of bioinformatics. Multiple alignments of PgaC sequences of different bacteria were used to identify conserved amino acid residues that might be critical for the functioning of the protein. Three-dimensional model of A. junii SH205 PgaC was generated for spatial visualization of amino acid residues. The analyses have shown that the protein PgaC has five conserved amino acids, Asp140, Asp233, Gln269, Arg272 and Trp273, critical for the activity of enzyme. Interaction of UDP-N-acetylglucosamine within the conserved pocket of glycosyltransferase was explored from molecular docking studies.

帕博利珠单抗治疗伴脑转移NSCLC患者的一项非随机、开放Ⅱ期试验的长期随访结果和生物标志物分析

背景与目的我们开展了一项帕博利珠单抗用于伴未治疗脑转移的非小细胞肺癌(non-small cell lung cancer,NSCLC)或黑色素瘤患者的疗效和安全性的II期试验,旨在评估程序性死亡受体1(programmed cell death 1,PD-1)抑制剂在中枢神经系统(central nervous system,CNS)中的疗效。中期结果已发表,现报道对NSCLC队列的更新分析结果。方法这是一项开放性、单中心、II期试验。纳入标准:年龄≥18岁,诊断为晚期NSCLC并伴有≥1个5 mm-20 mm脑转移病灶,既往从未治疗或之前放疗后进展,无神经系统症状,不需要激素治疗且美国东部肿瘤协作组(Eastern Cooperative Oncology Group,ECOG)<2分。患者每2周接受一次帕博利珠单抗(10 mg/kg)治疗。队列1为程序性死亡配体1(programmed cell death ligand 1,PD-L1)≥1%的患者,队列2为PD-L1<1%或未评估的患者。主要终点是脑转移患者缓解比例。所有经治患者均纳入疗效与安全性终点的分析。该研究已结束入组,并于Clinicaltrials.gov登记注册,注册号为NCT02085070。结果2014年3月31日-2018年5月21日,共42例患者接受治疗。中位随访时间为8.3个月(IQR:4.5个月-26.2个月)。队列1的37例患者中11例有脑转移缓解[29.7%(95%CI:15.9%-47.0%)]。队列2未观察到缓解。治疗相关的3级-4级不良事件(adverse events,AEs)包括2例肺炎、1例全身症状、1例结肠炎、1例肾上腺皮质功能不全、1例高血糖症和1例低钾血症。6例(14%)患者发生了治疗相关的严重不良事件,包括肺炎、急性肾损伤、低钾血症和肾上腺皮质功能不全。没有观察到治疗相关死亡病例。结论帕博利珠单抗治疗PD-L1≥1%的NSCLC伴脑转移患者有效,且对所有纳入的未经治疗的脑转移患者安全。需要进一步探索免疫治疗用于NSCLC合并CNS转移。

Active catalytic species generated in situ in zirconia incorporated hydrogen storage material magnesium hydride

This study explores how zirconia additive interacts with MgH_(2)to improve its hydrogen storage performance.Initially it is confirmed that the zirconia added MgH_(2)powder releases hydrogen at a temperature of about 50℃below that of the additive free MgH_(2).Subsequent tests by X ray diffraction(XRD)and infrared(IR)spectroscopy techniques reveal that the ZrO_(2) mixed MgH_(2)powder contains ZrHx(2<x>1.5)and MgO secondary phases.This observation is supported by the negative Gibbs free energy values obtained for the formation of ZrH_(2)/MgO from ZrO_(2)/MgH_(2)powder samples.An X ray photoelectron spectroscopy(XPS)study reveals that apart from Zr^(4+)cations,Zr^(2+) and zero valent Zr exist in the powder.Atomic force microscopy(AFM)study reveals that the average grain size is 20 nm and the elemental line scan profiles further proves the existence of oxygen deficient Zr bearing phase(s).This study strengthens the belief that functional metal oxide additives in fact chemically interact with MgH_(2)to make active in-situ catalysts in the MgH_(2)system.

Neglected scrub typhus:An updated review with a focus on omics technologies

Scrub typhus is a neglected disease and one of the most serious health problems in the Asia-Pacific region.The disease is caused by an obligate intracellular bacteria Orientia tsutsugamushi,which is transmitted by chigger bites or larval mite bites.Scrub typhus is a threat to billions of people worldwide causing different health complications and acute encephalitis in infants and growing children.The disease causes multiple organ failure and mortality rates may reach up to 70%due to a lack of appropriate healthcare.Currently available genome and proteome databases,and bioinformatics methods are valuable tools to develop novel therapeutics to curb the pathogen.This review discusses the state-of-the-art of information about Orientia tsutsugamushi-mediated scrub typhus and delineates the role of omics technologies to develop drugs against the pathogen.The role of proteome-wide in silico approaches for the identification of therapeutic targets is also highlighted.

An Effective Integrated Machine Learning Framework for Identifying Severity of Tomato Yellow Leaf Curl Virus and Their Experimental Validation

Tomato yellow leaf curl virus(TYLCV)dispersed across different countries,specifically to subtropical regions,associated with more severe symptoms.Since TYLCV was first isolated in 1931,it has been a menace to tomato industrial production worldwide over the past century.Three groups were newly isolated from TYLCV-resistant tomatoes in 2022;however,their functions are unknown.The development of machine learning(ML)-based models using characterized sequences and evaluating blind predictions is one of the major challenges in interdisciplinary research.The purpose of this study was to develop an integrated computational framework for the accurate identification of symptoms(mild or severe)based on TYLCV sequences(isolated in Korea).For the development of the framework,we first extracted 11 different feature encodings and hybrid features from the training data and then explored 8 different classifiers and developed their respective prediction models by using randomized 10-fold cross-validation.Subsequently,we carried out a systematic evaluation of these 96 developed models and selected the top 90 models,whose predicted class labels were combined and considered as reduced features.On the basis of these features,a multilayer perceptron was applied and developed the final prediction model(IML-TYLCVs).We conducted blind prediction on 3 groups using IML-TYLCVs,and the results indicated that 2 groups were severe and 1 group was mild.Furthermore,we confirmed the prediction with virus-challenging experiments of tomato plant phenotypes using infectious clones from 3 groups.Plant virologists and plant breeding professionals can access the user-friendly online IML-TYLCVs web server at https://balalab-skku.org/IML-TYLCVs,which can guide them in developing new protection strategies for newly emerging viruses.

利用中心原子价层轨道阐释软硬酸碱理论的原理与应用

软硬酸碱理论作为基础化学的重要理论,其在教学与教材中却存在定义不清、难以应用、适用范围不明、模棱两可等众多问题。借用前线轨道理论的观念,针对核心原子的外层轨道进行系统性讨论,并分类举例说明其适用范围与应用方式,以期对基础教学和相关科研有助。

Rice Interploidy Crosses Disrupt Epigenetic Regulation, Gene Expression, and Seed Development

Seed development in angiosperms requires a 2：1 maternal-to-paternal genome ratio （2m：lp） in the endo- sperm. When the ratio is disrupted, the seed development is impaired. Rice interploidy crosses result in endosperm failures, but the underlying molecular mechanisms remain unclear. Here, we report that the defective endosperm in rice interploidy crosses was associated with nonadditive expression of small RNAs and protein-coding genes. Interestingly, 24-nt small interfering RNAs were enriched in the 5＇ and 3＇ flanking sequences of nonadditively expressed genes in the interploidy crosses and were negatively associated with the expression of imprinted genes. Furthermore, some PRC2 family genes and DNA methylaUon-related genes including OsMETlb and OsCMT3a were upregulated in the 2x4 cross （polli- nating a diploid ＂mother＂ with a tetraploid ＂father＂） but repressed in the reciprocal cross. These different epigenetic effects could lead to precocious or delayed cellularization during endosperm development. Notably, many endosperm-preferred genes, including starch metabolic and storage protein genes during grain filling, were found to be associated with DNA methylation or H3K27me3, which are repressed in both 2×4 and 4 ×2 crosses. WUSCHEL homeobox2 （WOX2）-Iike （WOX2L）, an endosperm-preferred gene, was expressed specifically in the rice endosperm, in contrast to WOX2 expression in the Arabidopsis embryo. Disruption of WOX2L in transgenic rice by CRISPR/Cas9-mediated gene editing blocked starch and protein accumulation, resulting in seed abortion. In addition to gene repression, disrupting epigenetic process in the interploidy crosses also induced expression of stress-responsive genes. Thus, maintaining the 2m：lp genome ratio in the endosperm is essential for normal grain development in rice and other cereal crops.

Variable importance-weighted Random Forests

Background： Random Forests is a popular classification and regression method that has proven powerful for various prediction problems in biological studies. However, its performance often deteriorates when the number of features increases. To address this limitation, feature elimination Random Forests was proposed that only uses features with the largest variable importance scores. Yet the performance of this method is not satisfying, possibly due to its rigid feature selection, and increased correlations between trees of forest. Methods： We propose variable importance-weighted Random Forests, which instead of sampling features with equal probability at each node to build up trees, samples features according to their variable importance scores, and then select the best split from the randomly selected features. Results： We evaluate the performance of our method through comprehensive simulation and real data analyses, for both regression and classification. Compared to the standard Random Forests and the feature elimination Random Forests methods, our proposed method has improved performance in most cases. Conclusions： By incorporating the variable importance scores into the random feature selection step, our method can better utilize more informative features without completely ignoring less informative ones, hence has improved prediction accuracy in the presence of weak signals and large noises. We have implemented an R package ＂viRandomForests＂ based on the original R package ＂randomForest＂ and it can be freely downloaded from http：// zhaocenter.org/software.

Distinct transcriptomic landscapes of cutaneous basal cell carcinomas and squamous cell carcinomas

The majority of non-melanoma skin cancer(NMSC)is cutaneous basal cell carcinoma(BCC)or squamous cell carcinoma(SCC),which are also called keratinocyte carcinomas,as both of them originate from keratinocytes.The incidence of keratinocyte carcinomas is over 5 million per year in the US,three-fold higher than the total incidence of all other types of cancer combined.While there are several reports on gene expression profiling of BCC and SCC,there are significant variations in the reported gene expression changes in different studies.One reason is that tumor-adjacent normal skin specimens were not included in many studies as matched controls.Furthermore,while numerous studies of skin stem cells in mouse models have been reported,their relevance to human skin cancer remains unknown.In this report,we analyzed gene expression profiles of paired specimens of keratinocyte carcinomas with their matched normal skin tissues as the control.Among several novel findings,we discovered a significant number of zinc finger encoding genes up-regulated in human BCC.In BCC,a novel link was found between hedgehog signaling,Wnt signaling,and the cilium.While the SCC cancerstem-cell gene signature is shared between human and mouse SCCs,the hair follicle stem-cell signature of mice was not highly represented in human SCC.Differential gene expression(DEG)in human BCC shares gene signature with both bulge and epidermal stem cells.We have also determined that human BCCs and SCCs have distinct gene expression patterns,and some of them are not fully reflected in current mouse models.

Discovery of potential biomarkers for human atherosclerotic abdominal aortic aneurysm through untargeted metabolomics and transcriptomics

Abdominal aortic aneurysm(AAA)and atherosclerosis(AS)have considerable similarities in clinical risk factors and molecular pathogenesis.The aim of our study was to investigate the differences between AAA and AS from the perspective of metabolomics,and to explore the potential mechanisms of differential metabolites via integration analysis with transcriptomics.Plasma samples from 32 AAA and 32 AS patients were applied to characterize the metabolite profiles using untargeted liquid chromatography-mass spectrometry(LC-MS).A total of 18 remarkably different metabolites were identified,and a combination of seven metabolites could potentially serve as a biomarker to distinguish AAA and AS,with an area under the curve(AUC)of0.93.Subsequently,we analyzed both the metabolomics and transcriptomics data and found that seven metabolites,especially 2’-deoxy-D-ribose(2 d DR),were significantly correlated with differentially expressed genes.In conclusion,our study presents a comprehensive landscape of plasma metabolites in AAA and AS patients,and provides a research direction for pathogenetic mechanisms in atherosclerotic AAA.

Sarve:synthetic data and local differential privacy for private frequency estimation

The collection of user attributes by service providers is a double-edged sword.They are instrumental in driving statistical analysis to train more accurate predictive models like recommenders.The analysis of the collected user data includes frequency estimation for categorical attributes.Nonetheless,the users deserve privacy guarantees against inadvertent identity disclosures.Therefore algorithms called frequency oracles were developed to randomize or perturb user attributes and estimate the frequencies of their values.We propose Sarve,a frequency oracle that used Randomized Aggregatable Privacy-Preserving Ordinal Response(RAPPOR)and Hadamard Response(HR)for randomization in combination with fake data.The design of a service-oriented architecture must consider two types of complexities,namely computational and communication.The functions of such systems aim to minimize the two complexities and therefore,the choice of privacy-enhancing methods must be a calculated decision.The variant of RAPPOR we had used was realized through bloom flters.A bloom filter is a memory-efficient data structure that offers time complexity of O(1).On the other hand,HR has been proven to give the best communication costs of the order of log(b)for b-bits communication.Therefore,Sarve is a step towards frequency oracles that exhibit how privacy provisions of existing methods can be combined with those of fake data to achieve statistical results comparable to the original data.Sarve also implemented an adaptive solution enhanced from the work of Arcolezi et al.The use of RAPPOR was found to provide better privacy-utility tradeoffs for specific privacy budgets in both high and general privacyregimes.

State-of-the-art developments in metal and carbon-based semiconducting nanomaterials： applications and functions in spintronics, nanophotonics, and nanomagnetics

Nanomaterials composed of metals and metal alloys are the most valuable components in emerging micro- and nano-electronic devices and innovations to date. The composition of these nanomaterials, their quantum chemical and physical properties, and their production methods are in critical need of summarization, so that a complete state of the art of the present and future of nanotechnologies can be presented. In this review, we report on the most recent activities and results in the fields of spintronics, nanophotonics, and nanomagnetics, with particular emphasis on metallic nanoparticles in alloys and pure metals, as well as in organic combinations and in relation to carbon-based nanostructures. This review shows that the combinatory synthesis of alloys with rare metals, such as scandium, yttrium, and rare earths imparts valuable qualities to high-magnetic-field compounds, and provides unique properties with emphasis on nanoelectronic and computational components. In this review, we also shed light on the methods of synthesis and the background of spintronic, nanomagnetic, and nanophotonic materials, with applications in optics, diagnostics, nanoelectronics, and computational nanotechnology. The review is important for the industrial development of novel materials, and for summarizing both fabrication and manufacturing methods, as well as principles and functions of metallic nanoparticles.

uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction

In the era of antibiotic resistance,in silico prediction of bacterial resistome pro-files,likely to be associated with inactivation of new potential antibiotics is of utmost impor-tance.Despite this,to the best of our knowledge,no tool exists for such prediction.Therefore,under the rationale that drugs with similar structures have similar resistome profiles,we devel-oped two models,a deterministic model and a stochastic model,to predict the bacterial re-sistome likely to neutralize uncharacterized but potential chemical structures.The current version of the tool involves the prediction of a resistome for Escherichia coli and Pseudomonas aeruginosa.The deterministic model on omitting two diverse but relatively less characterized drug classes,polyketides and polypeptides showed an accuracy of 87%,a sensitivity of 85%,and a precision of 89%,whereas the stochastic model predicted antibiotic classes of the test set compounds with an accuracy of 72%,a sensitivity of 75%,and a precision of 83%.The models have been implemented in both a standalone package and an online server,uCAREChemSuite-CLI and uCARE Chem Suite,respectively.In addition to resistome prediction,the online version of the suite enables the user to visualize the chemical structure,classify compounds in 19 pre-defined drug classes,perform pairwise alignment,and cluster with database compounds using a graphical user interface.

Predictability of polygenic risk score for progression to dementia and its interaction with APOEε4 in mild cognitive impairment

Background:The combinatorial efect of multiple genetic factors calculated as a polygenic risk score(PRS)has been studied to predict disease progression to Alzheimer’s disease(AD)from mild cognitive impairment(MCI).Previous studies have investigated the performance of PRS in the prediction of disease progression to AD by including and excluding single nucleotide polymorphisms within the region surrounding the APOE gene.These studies may have missed the APOE genotype-specifc predictability of PRS for disease progression to AD.Methods:We analyzed 732 MCI from the Alzheimer’s Disease Neuroimaging Initiative cohort,including those who progressed to AD within 5 years post-baseline(n=270)and remained stable as MCI(n=462).The predictability of PRS including and excluding the APOE region(PRS_(+APOE) and PRS_(−APOE))on the conversion to AD and its interaction with the APOEε4 carrier status were assessed using Cox regression analyses.Results:PRS_(+APOE)(hazard ratio[HR]1.468,95%CI 1.335-1.615)and PRS_(−APOE)(HR 1.293,95%CI 1.157-1.445)were both associated with a signifcantly increased risk of MCI progression to dementia.The interaction between PRS_(+APOE) and APOEε4 carrier status was signifcant with a P-value of 0.0378.The association of PRSs with the progression risk was stronger in APOEε4 non-carriers(PRS_(+APOE):HR 1.710,95%CI 1.244-2.351;PRS_(−APOE):HR 1.429,95%CI 1.182-1.728)than in APOEε4 carriers(PRS_(+APOE):HR 1.167,95%CI 1.005-1.355;PRS_(−APOE):HR 1.172,95%CI 1.020-1.346).Conclusions:PRS could predict the conversion of MCI to dementia with a stronger association in APOEε4 noncarriers than APOEε4 carriers.This indicates PRS as a potential genetic predictor particularly for MCI with no APOEε4 alleles.

Integrative modeling of transmitted and de novo variants identifies novel risk genes for congenital heart disease

Background:Whole-exome sequencing(WES)studies have identified multiple genes enriched for de novo mutations(DNMs)in congenital heart disease(CHD)probands.However,risk gene identification based on DNMs alone remains statistically challenging due to heterogenous etiology of CHD and low mutation rate in each gene.Methods:In this manuscript,we introduce a hierarchical Bayesian framework for gene-level association test which jointly analyzes de novo and rare transmitted variants.Through integrative modeling of multiple types of genetic variants,gene-level annotations,and reference data from large population cohorts,our method accurately characterizes the expected frequencies of both de novo and transmitted variants and shows improved statistical power compared to analyses based on DNMs only.Results:Applied to WES data of 2,645 CHD proband-parent trios,our method identified 15 significant genes,half of which are novel,leading to new insights into the genetic bases of CHD.Conclusion:These results showcase the power of integrative analysis of transmitted and de novo variants for disease gene discovery.

从磷酸酯化学刍议各类磷酸酶和三磷酸核苷酶的生物化学转化与机制

磷作为一切生物体的必需元素,参与了包括生命体能量代谢、结构调控、遗传信息传递等在内的必要过程,其重要性不言而喻。然而,在国内基础学科教学过程中,基于酶促反应的调控机制和反应机理被拆分到众多生化专业相关的课程中,并未能得到系统性的剖析与讲解。本文从基础磷酸酯和磷酸酐的化学结构及反应特性入手,分别讨论了生物体中磷酸酯相关的调控酶类,并对最重要的一类磷酸酐——三磷酸腺苷在生物体内的转化关系做了系统性的讲解及分析。作为对磷元素相关的生命化学过程的梳理归纳,希望对化学及生命科学的教学与科研实验设计有所助益。